An integrated, end-to-end big data and analytics platform is critical to an organization's ability to gain real-time insights from a growing number of sources.
The digital age has introduced a growing need to tap into data and drive decision making on a real-time basis. Organizations that succeed gain a competitive edge through improved operational efficiency, lower costs and improved profitability.
A recently released brief from EY, "Why an Integrated Platform Is the Key to Real-time Insights," notes that the key to success is an integrated platform. While this may seem like a straightforward concept, achieving results can prove elusive.
The author of the report, Scott Schlesinger, a partner and principal in EY's IT Advisory Practice, says that an integrated, end-to-end big data and analytics platform is critical to an organization's ability to gain real-time insights. This next-gen framework must plug in data from a growing number of sources and incorporate it throughout its life cycle.
At the center of this model are systems, processes and workflows that allow the organization to spot the right data at the right time—and understand which data is relevant for a specific business issue.
Of course, all of this is easier said than done. Among other things, it requires CIOs to take a broader and more creative approach.
As Schlesinger points out, Hadoop can store massive quantities of data and help an enterprise put huge data sets to work while trimming storage costs. However, it can also prove "somewhat cumbersome to administer and require a fairly unique set of programming skills." What's more, there's frequently a lag in the development of Hadoop-specific applications.
On the other hand, Oracle and SAP HANA run indexing and other tasks in physical memory, thus speeding processing but boosting costs.
The answer, he says, lies in a blended approach that strategically places the right tool and technology at the right place. This integrated big data and analytics platform must also connect to legacy business applications such as ERP, CRM and HR and home in on industry-specific needs and requirements.
In manufacturing or energy, this might mean predictive asset management fueled by large volumes of unstructured data. In retailing, it could translate into real-time point-of-sale (POS) and smartphone connectivity.
Finally, Schlesinger believes that a more agile and modular framework must extend into a supply chain. "Traditional business intelligence platforms alone can no longer keep pace with the needs that shape changing commerce," he advises.
"Emerging technologies, such as Hadoop, are a prerequisite to lower-cost data management. In-memory solutions, such as SAP HANA, offer speed-of-thought analytics. When combined and integrated across the entire organizational data platform, true, value-added, integrated, end-to-end business intelligence is achieved."
Samuel Greengard, a contributor to CIO Insight, writes about business, technology and other topics. His forthcoming book, The Internet of Things (MIT Press), will be released in the spring of 2015.
This article was originally published on 01-09-2015
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